In choosing a color palette, it is necessary to take into account the needs of color vision impaired users, in order to make information and services accessible to a broader audience. This means researching a space of color palettes aimed at finding a color combination which represents a good trade-off between aesthetics and accessibility requirements. In this paper, we present a solution based on genetic algorithms. Experimental results highlight this approach to be an efficient and at the same time effective way to assist user interface designers by suggesting appropriate variations of color palettes.
Con este trabajo se pretenden determinar los factores que influyen de forma significativa como barreras para la aplicación de Revenue Management-RM-(también denominado Yield Management). Con este objetivo, se analiza la influencia de su conocimiento, implantación y de la dimensión del hotel, sobre las dificultades experimentadas por los hoteles en dos momentos, al inicio del proceso de la implantación de RM y en el momento actual. El estudio se realiza sobre el censo de hoteles de cuatro y cinco estrellas de la provincia de Sevilla. Se ha constatado, de un lado, la influencia significativa que ejerce la disponibilidad de un software de RM sobre las dificultades al inicio del proceso de implantación y, de otro, la influencia también significativa de la implantación de RM, dimensión del hotel, pertenencia a una cadena y dimensión de la cadena, sobre las dificultades a las que actualmente deben enfrentarse los hoteles para la aplicación de RM. Adicionalmente se han identificado aquellos obstáculos que resultan críticos a la hora de aplicar RM en el sector hotelero dependiendo del perfil del hotel. Con ellos el establecimiento podrá hacer una evaluación previa de sus fortalezas, debilidades y áreas de actuación prioritarias para la implantación de RM.
Gesture recognition is very important for Human-Robot Interfaces. In this paper, we present a novel depth based method for gesture recognition to improve the interaction of a service robot autonomous shopping cart, mostly used by reduced mobility people. In the proposed solution, the identification of the user is already implemented by the software present on the robot where a bounding box focusing on the user is extracted. Based on the analysis of the depth histogram, the distance from the user to the robot is calculated and the user is segmented using from the background. Then, a region growing algorithm is applied to delete all other objects in the image. We apply again a threshold technique to the original image, to obtain all the objects in front of the user. Intercepting the threshold based segmentation result with the region growing resulting image, we obtain candidate objects to be arms of the user. By applying a labelling algorithm to obtain each object individually, a Principal Component Analysis is computed to each one to obtain its center and orientation. Using that information, we intercept the silhouette of the arm with a line obtaining the upper point of the interception which indicates the hand position. A Kalman filter is then applied to track the hand and based on state machines to describe gestures (Start, Stop, Pause) we perform gesture recognition. We tested the proposed approach in a real case scenario with different users and we obtained an accuracy around 89,7%. 1 Introduction Nowadays, with robots entering in our daily lives, it is becoming important to provide the users a simple and intuitive way to interact with them. Human-Robot interactions has already proved to be a major field in robotics with an
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.